code: def test_can_construct_image_embeddings_from_params(
      image_embeddings, image_params_dict
  ):
      assert (
          image_embeddings.embeddings.image_embeddings.in_features
          == image_params_dict["feature_size"]
      )
      assert (
          image_embeddings.embeddings.image_embeddings.out_features
          == image_params_dict["embedding_size"]
      )
      assert (
          image_embeddings.embeddings.location_embeddings.out_features
          == image_params_dict["embedding_size"]
      )
      assert image_embeddings.dropout.p == image_params_dict["dropout"]
  
imports: import copy
  import pytest
  import torch
  from torch.testing import assert_allclose
  from transformers import AutoModel
  from transformers.models.bert.configuration_bert import BertConfig
  from transformers.models.bert.modeling_bert import BertEmbeddings
  from transformers.models.albert.configuration_albert import AlbertConfig
  from transformers.models.albert.modeling_albert import AlbertEmbeddings
  from allennlp.common import Params, FromParams
  from allennlp.modules.transformer import TransformerEmbeddings, ImageFeatureEmbeddings, TransformerModule
label_desc: Use image node_id 16 for calling a global function with example usage: test_can_construct_image_embeddings_from_params(image_embeddings, image_params_dict) without return types